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Ignite Insights

as a Service

Meaningful is an intelligence operating system for market research and customer insight. 

 

It is built on a single architectural principle: insight should be connected, contextualized, and preserved over time.

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By unifying data across sources, preserving institutional memory, and enabling high-quality synthesis at scale, insights can be compared, connected, and reinterpreted across sources. 

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The result is the foundational infrastructure for an Insights as a Service (IaaS) operating model — where knowledge compounds, context endures, and strategic clarity strengthens over time.

Reimagined

Research

Teams are drowning in dashboards, scattered insights, and siloed tools. Primary research lives in one place, competitive intelligence in another, market context in yet another, and none of it connects cleanly. The burden of integration falls on already-stretched research teams, who spend more time compiling than interpreting. The real bottleneck is the ability to interpret, integrate, and act on what the data is trying to say.

Meaningful reimagines research where diverse inputs flow into a shared analytical context, their integrity preserved, and their connections amplified. Where insight compounds, context endures and institutional memory grows. Call it the 'researcher's companion' Meaningful frees us to focus on the work that truly matters. Adding unmatched value to any organization. 

Designed for human-in-the-loop intelligence, Meaningful orchestrates data and synthesis while leaving interpretation, strategy, and recommendations firmly in human hands. Research stops being episodic. It becomes continuous. Connected. 

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Deep Integration

Meaningful combines data sources into a shared interpretive environment.

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Common Framewords

Common analytical frameworks are applied across disparate data sources.

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Insights Compounded

Insight accumulates rather than resets between projects.

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Preservation of Memory

Context and institutional memory over time is preserved over time.

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Continuous Intelligence

Meaningful moves from episodic analysis to continuous intelligence.

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Unified System

Traditional research models are constrained by their structure. Context is often lost. Prior insight is underutilized. Organizations pay to rediscover what they already know.


Meaningful addresses this by treating insight as a continuous operating system, not a sequence of deliverables.

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Rather than commissioning discrete projects that reset context each time, Meaningful enables organizations to operate an always-on insight capability that accumulates understanding, preserves memory, and evolves alongside the business.

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By providing continuity across studies, consistent interpretation across data sources, preservation of institutional memory, and faster, smarter decision-making, Meaningful enables a shift away from episodic research delivery toward continuous intelligence stewardship.
 

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Customer Intelligence Layer for Brands 

Meaningful is purpose-built for market research. Its architecture also supports a broader role.


For brands, Meaningful functions as a customer intelligence layer—a system that continuously integrates signals from across the organization and the market to build a coherent, evolving understanding of customers.

 

This includes: 

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  • Primary research conducted internally or by partners

  • Ongoing social and cultural signals

  • Competitive and market intelligence

  • Internal documents, historical research, and knowledge assets

  • Client-owned data ingested via secure connectors

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Insights as a Service (IaaS) for Agencies

For agencies and insight partners, Meaningful  enables Insights as a Service (IaaS) where agencies retain ownership of the client relationship, strategic framing, interpretation, and recommendations. 

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In this way, Meaningful is not positioned instead of agencies, researchers, or analysts. It is the researcher's companion, designed to bring out the best in everyone by removing structural friction and enabling deeper, more durable insight.

Unified System

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Unify data into a single system to enable continuous customer intelligence that does not reset but compounds.

Customer Intelligence Layer

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A customer intelligence layer for brands to maintain evolving understanding of their markets.

Insights as a Service (IaaS)

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An infrastructure foundation for Insights as a Service (IaaS) partnerships that deepen over time.

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Insights as a Service 

Insights as a Service (IaaS) represents a shift away from episodic research delivery toward continuous intelligence stewardship. 
 

Meaningful provides the infrastructure that makes this model possible in practice.

Insights as a Service with Meaningful

​Meaningful enables a powerful operating model: Insights as a Service (IaaS).

 

With the capability to retain and connects insight across time, organizations operating IaaS gain several structural advantages:

  • New research is interpreted in the context of everything that came before

  • Emerging signals can be detected earlier

  • Hypotheses can be revisited and tested as new data arrives

  • Strategic conversations are grounded in accumulated evidence rather than isolated findings

Insight becomes cumulative. Decision quality improves not because any single study is better, but because understanding deepens over time.​

Iaas Model

In an IaaS model, Meaningful acts as the central intelligence layer that sits between data sources and human decision-makers.

In an IaaS model:
 

  • Insight is continuous rather than project-based

  • Learning compounds instead of resetting

  • Context becomes a strategic asset

  • Human expertise is amplified rather than replaced

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Continuous Insights

Insight is continuous rather than project-based

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Strategic Asset

Context becomes a strategic asset

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Intelligence Compounded

Learning compounds instead of resetting

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Human Expertise

Human expertise is amplified rather than replaced

In an IaaS model, Meaningful acts as the central intelligence layer that sits between data sources and human decision-makers.

The structural problem IaaS solves

Traditional research models are constrained by their structure.


Each project typically:

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  • Begins with a fresh briefing

  • Requires reorientation to historical context

  • Rebuilds understanding from partial information

  • Produces a static output

  • Ends with insight dispersed across decks, documents, and inboxes


Even when individual projects are high quality, the system as a whole does not learn. Context is lost. Prior insight is underutilized. Organizations repeatedly pay to rediscover what they already know.


IaaS addresses this by treating insight as a continuously operating system, not a sequence of deliverables.

Meaningful’s role in the IaaS ecosystem

In an IaaS model, Meaningful acts as the central intelligence layer that sits between data sources and human decision-makers.

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Because Meaningful retains and connects insight across time, organizations operating IaaS gain several structural advantages:

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  • New research is interpreted in the context of everything that came before

  • Emerging signals can be detected earlier

  • Hypotheses can be revisited and tested as new data arrives

  • Strategic conversations are grounded in accumulated evidence rather than isolated findings

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Insight becomes cumulative. Decision quality improves not because any single study is better, but because understanding deepens over time.

A shared intelligence foundation for multiple stakeholders

Another key characteristic of IaaS is that it supports multiple stakeholders simultaneously.

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The same Meaningful instance can serve:

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  • Agency teams delivering insight and advisory services

  • Brand-side research and strategy teams

  • ​Product, marketing, and executive stakeholders

 

Each group interacts with the same underlying intelligence layer, but at different levels of abstraction and responsibility. This reduces translation loss, misalignment, and duplicated effort.

 

Meaningful ensures that everyone is working from a shared, continuously updated understanding of reality, even as their roles differ.

Meaningful Journey. Each step is optional.
The user is in control

OBJECTIVE

Research Challenge

Identify research challenge / objective. Add as much context as you like to optimize results.​

DIRECTION

Research Plan

Takes your input and creates a research plan based on an integrated research approach.

SECONDARY RESEARCH

Research the Market

Gathers deep secondary data such as industry reports and market data to help shape primary research or to add further context to gathered information.

SECONDARY RESEARCH

External Data Connectors

Integrate your data such as CRM, analytics, support spreadsheets,
and reports

DIGITAL SIGNALS

Social Scraping

Track and monitor sentiment across various channels such as Reddit, Twitter, reviews, and forums in real time.

DIGITAL SIGNALS

AI Perception

Understand how ChatGPT, Claude, and other AI systems perceive your brand.

PRIMARY RESEARCH

Quantitative Survey

Layer in your primary research. You can easily import data from your quantitative survey such as Qualtrics or Forsta.

PRMARY RESEARCH

Meaningful Conversations

Run a Conversation. It's Meaningful's AI moderated interviews for gathering qualitative data at scale. 

INTEGRATION & ANALYSIS

Live Sythesis

Takes minutes what would typically be done in days or weeks. With the click of a button, one complete story emerges from multiple data streams.

OUTPUT

Insights Dashboard

Multiple data sources unified for a deeper understanding of your research goals and delivered through a clear, intuitive dashboard.

PROBE & EXPLORE

Chat with Data 

All sources are brought together in a single analytical context. Interact with your datasets, ask questions.

PROBE & EXPLORE

Threads

Test hypotheses against your research. Ask a question, upload a concept, and see what the evidence supports with full traceability across sources.

CUSTOMIZE & CREATE

Story

Your personal workspace for organizing research insights. Collect highlights from any analysis and arrange them however you want to tell your story.

Until your next Meaningful Journey!
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Meaningful

Core Capabilities

CORE CAPABILTIES

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QUALITATIVE

AI-moderated qualitative conversations + human-moderated interview ingestion and analysis

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SOCIAL & CULTURAL SIGNALS

Social listening as continuous qualitative signal stream that complements primary research and grounds insight in real-world language and behavior.

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QUANTITATIVE

Quantitative survey ingestion and integration. Findings are integrated and interpreted to enrich ongoing synthesis

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DATA CONNECTORS

Flexible system of external data connectors and document ingestion, allowing organizations to unify all relevant sources of intelligence

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MARKET INTELLIGENCE

Provides secondary research and strategic intelligence structured around strategic questions

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LIVE SYNTHESIS

All intelligence is integrated into a continuously updated view of what’s well-supported, emerging, and uncertain or contradictory.

LATEST MEANINGFUL FEATURES

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THREADS

Mechanism for explicit, hypothesis-driven analysis.
Test strategic ideas, assumptions, and concepts.

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OBSERVABILITY

Framework for evaluating the quality, integrity, and reliability of reasoning in synthesis and analysis.

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STORY

Personal workspace for organizing research insights. Customize outputs to tell your story.

Reach out for more information about Meaningful's latest innovations, including Meaningful Agency

See How Meaningful Works

Along with providing dashboard reports, Meaningful enables brands to maintain a living, queryable understanding of customer needs, perceptions, and behaviors that evolves as new data arrives.

Along with providing dashboard reports, Meaningful enables brands to maintain a living, queryable understanding of customer needs, perceptions, and behaviors that evolves as new data arrives.

Meaningful Case Studies

From complex B2B challenges to fast-turn creative testing, Meaningful has become an essential part of our research workflow. Below are recent projects using Meaningful. Each project demonstrates how smarter workflows, and Meaningful's AI-powered integrated research platform translate directly into successful outcomes (and cost and time savings). 

B2B: Emerging Technology

EMERGING TECHNOLOGY

Objective: Understanding messaging and solution requirements for emerging technology in the US.

Audience: Purchase decision-makers (manager level+) in the emerging technology space across multiple industry verticals.

Approach: Online quantitative survey layered with secondary data (market analysis and social scraping) to validate findings and expand recommendations for this niche industry.

Meaningful Application: Meaningful was used to integrate all data sources and create profiles for each of the different verticals. What would have taken weeks took hours. We also made use of Meaningful's "Chat with data" function. 

Health: Creative Testing

HEALTH SYSTEM

Objective: Creative testing for a health system in the US. Testing audience reaction before full production. 

Audience: Parents of children under the age of 18 in certain geographic regions. 

Approach: Online screener + Conversations to get in-depth insight into audience reaction on a few short videos. Respondents were interviewed in a conversational style and asked to give their honest feedback. The conversation also allowed us to get in depth feedback validate the creative direction and provide easy optimizations for the creative team. 

Meaningful Application: Meaningful's Conversation was used for the in-depth interviews. Results were delivered to our client via a link that was as easy to read as it was to navigate. The dashboard featured key findings, highlights, sentiment, themes, representative quotes, overall findings, and more, including the transcript of each respondent so the client could view as well.

Consumer: Concept Testing

WELL ESTABLISHED SNACK BRAND

Objective: Test audience reception to two potential campaigns and messages from each campaign for a well established popcorn brand.

Audience: Consumer study of purchasers of salty snacks, ages 18-60 in the US.

Approach: Online quantitative survey.

Meaningful Application: Findings from the quantitative survey showed a very close tie between the two concepts. We uploaded the raw data from our quantitative survey and used Meaningful to gather consumer trends and social insights for the industry.  We then ran a synthesized review to recommend a creative decision for the client that was grounded in primary and secondary research.

Retail Media: Visitor Intercept

POP-UP STORE INTERCEPT INTERVIEWS VIA QR CODE

Objective: Collect real-time consumer feedback on brands among visitors of retail pop-up event. 

Audience: Visitors of the retail pop-up (invite-only event) which included retailers, buyers, and influencers.

Approach: Meaningful's Conversation was used to create quick conversational style surveys for the different brands represented at the pop-up store. The survey was administered to visitors of the pop-up using a QR code.  

Meaningful Application: Each survey was customized per brand and the results were available by individual brand dashboards.  Additionally, data was merged across brands into one report and layered with secondary data to generate a unified trend analysis. The dashboard featured core consumer insights, trial behavior dynamics, strategic recommendations, key findings, metrics, trends, insights and more including a detailed breakdown of the individual brands. All the data was consolidated into one clean and easy to read dashboard. 

Meaningful is designed for human-in-the-loop intelligence. It orchestrates data and analysis so that teams can focus on interpretation, synthesis, and decision-making.

Contact us

​Meaningful transforms research into a living, evolving intelligence engine — one that captures real human nuance and compounds over time. By scaling depth, not just data, Meaningful empowers brands, agencies, and researchers to move beyond surface-level answers and deliver strategic clarity and insight their clients can’t get anywhere else.

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thinqinsights was an early adopter of Meaningful and it has become an indispensable part of our research process. Partnering with Meaningful, we not only thinqinsights, we ignite insights. 

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For more information about Meaningful products, pricing or to request a demo, or just to chat about Meaningful, contact us.

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